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ULID Generator

Generate Universally Unique Lexicographically Sortable Identifiers with high performance

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Snowflake ID Generator

Generate highly-performant, 64-bit distributed unique identifiers (Snowflake IDs). Originally developed by Twitter, Snowflake IDs are sortable by time and fit in a standard 64-bit unsigned integer.

Snowflake ID Generator & Anatomy Visualizer

Generate, parse, and visualize distributed 64-bit Snowflake IDs

Snowflake Configuration
0
0
0
Snowflake Parser / Decoder

Bit-Level Structural Anatomy (64 bits)

Hover over the sections below to see how Snowflake IDs compress dynamic temporal, machine, and sequential bits into a singular positive 64-bit integer.

Sign Bit (1 bit)
0
Timestamp (41 bits)
2026-05-29 17:06:06.000 UTC ms since epoch: 0
Datacenter (5 bits)
0
Worker / Machine (5 bits)
0
Sequence (12 bits)
0
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Snowflake ID vs UUID vs ULID

Feature Snowflake ID ULID UUID v4
Data Type Yes 64-bit Integer (BigInt) Yes 128-bit String Yes 128-bit String (Hex)
Time-Sortable Yes (Millisecond precision) Yes (Millisecond precision) No
Distributed safe Yes (Requires Machine ID) Yes (Randomness component) Yes (Cryptographic entropy)
Length / Representation Yes 19-character digit string Yes 26 Crockford Base32 chars No 36 hex-formatted chars
Ideal Database indexing Yes Extremely High (Native Integer) Yes High (String type) No Moderate (Hex String)

Anatomy of a Snowflake ID

A standard Snowflake ID is represented as a 64-bit integer, and its bits are allocated as follows:

  • Sign bit (1 bit): Always 0 to ensure the generated number is positive.
  • Timestamp (41 bits): Millisecond epoch precision, providing up to 69 years of unique timestamps based on a custom Epoch.
  • Machine/Node ID (10 bits): Identifies the server instance generating the ID, supporting up to 1024 unique instances.
  • Sequence (12 bits): Local counter incremented within the same millisecond to prevent collisions, supporting up to 4096 unique IDs per millisecond per machine.

Ideal Use Cases

  • High-volume relational database primary keys (MySQL, PostgreSQL) where integer indexes are faster than strings.
  • Distributed logging or analytics systems that require time-sortable event indexing.
  • Large microservice environments where individual nodes generate unique IDs without centralized coordination.
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